Failure Happens Research Articles

Sweep frequency response analysis of three-phase induction motors using high frequency circuit model

Three-phase induction motor (TPIM) is one of the most important and expensive component in many industries. If a failure happens in service, the impact can be far reaching. Resulting in prolonged downtimes and expensive repairs. Sweep frequency response analysis (SFRA) is a new method that is being proposed to assess the condition of windings in motors. This paper proposes an approach for measuring the SFRA of the TPIMs using its high frequency (HF) circuit model. It also introduces an easy and efficient way to estimate the parameter values of the HF model based on the data from the SFRA test. The method first simulates the HF model and then aligns the simulated SFRA curve with the experimental one by adjusting the parameter values. This adjustment is based on individual parameter effects on the SFRA signature. The aim of this paper is to understand the SFRA signatures of TPIMs by using both experimental and simulation methods. SFRA measurements are carried out on two TPIMs (1 HP and 3 HP) under the same phases (U1U2, V1V2, W1W2) and different phase connections (U1V1, U1W1, V1W1). This paper utilizes two statistical indicators, Absolute Sum of Logarithmic Error (ASLE) and Correlation Coefficient (CC), for interpreting SFRA signatures. The CC values, ranging from 0.98 to 0.99, and the ASLE values, between 0.4 and 1.5 dB, indicate a good agreement between the measured and simulated SFRA signatures. This validates that the proposed HF model is accurate and can be applied to SFRA measurements for any rating of TPIM. This accuracy is verified in this paper using two different rating TPIMs.

Study of hydrogen embrittlement in steels using modified pressurized disks

The integration of hydrogen into natural gas pipelines presents challenges due to Hydrogen Embrittlement (HE), requiring critical material selection and testing methods. One such test is the Disk Pressure Test (DPT), which consists in pressurizing a clamped disk to failure. However, failure happens often at the clamping zone, making analysis difficult. This study aims to develop new disk geometries to control failure location while maintaining the test setup. Using two steel grades (a vintage X52 pipeline steel and a modern E355 modified steel with potential for pipeline use), new disk geometries were tested under helium and hydrogen at various pressure rise rates. Results show successful displacement of failure away from the clamping zones, demonstrating the effectiveness of the new geometries. Hydrogen embrittlement is demonstrated by comparing failure pressures under helium and hydrogen at various pressure rise rates. Using both material testing and simulation, this study provides insights into hydrogen embrittlement.

Unreliable M[X]/G(P1,P2)/1 feedback retrial queues with combined working vacation

The study examines M[X]/G(P1,P2)/1 feedback retrial queues coupled with starting failure, repair, delay to repair, working vacation, and general retrial times. Also, it explores how different batch sizes affect performance and how bulk arrival affects system behavior. When the server is not in use, a single customer initiates the system while the remaining customers transition to a state of orbit. A new customer must turn on the server to provide two phases of mandatory service at any time. The server could have starting issues. If the service is successfully started (with likelihood α), the customer receives service immediately. In the absence of that, the likelihood of starting failure happens (with likelihood 1−α=α¯). The server was taken for repair with some delay and that customer was transported to an orbital location. When the server was busy or unavailable, the arriving customers queued by FCFS in the orbit. We also discuss the idea of reworking with probability p, and restarting unsuccessful service attempts to improve customer happiness and service efficiency. We also introduce the concept of working vacation, which permits servers to temporarily stop providing services, affecting system performance and availability at both peak and off-peak times. A supplementary variable technique was adopted for the system's and orbit size's probability-generating function. Various performance measurements were provided with appropriate numerical examples.

Micromechanical analysis of fiber-reinforced ceramic matrix composites by a geometrically nonlinear hierarchical quadrature element model

The stress fields of fiber-reinforced ceramic matrix composites (CMCs) under longitudinal tension are predicted using a non-linear hierarchical quadrature element method (HQEM) in this work. The HQEM combines the differential quadrature method (DQM) with the hierarchical finite element method (HFEM), which is a typical p-version finite element method (FEM). High-order interpolation functions of the HQEM allow accurate evaluation of stress distribution. Fiber, matrix, and interfaces of the CMCs are modeled as linear elastic materials that may have large displacements. The nonlinear HQEM estimation of CMCs stress distributions are validated by comparing with analytical results obtained using classical BHE shear-lag model. Stress distribution in three characteristic stages in the damage evolution process, namely, interface perfectly bonded, interface debonding, and fiber failure are investigated. It is shown that when fiber failure happens, geometric non-linearity must be considered to avoid excessive stress concentration. Furthermore, the stress distribution within three-dimensional cylindrical CMCs cell is studied, which sheds light on the future exploration of three-dimensional CMCs analyses.

Identifying multiple synergistic factors on the susceptibility to stress relaxation cracking in variously heat-treated weldments

The 347H austenitic stainless steel has been widely used for pressure vessels and pipeline (PVP) applications due to its excellent creep and corrosion resistance, which fit ideally to the harsh conditions in petrochemical industries, fossil fuel or nuclear power plants, and modern energy storages. However, a failure mode has been commonly observed with cracks emerging at the heat affected zone (HAZ) of weldments during post-weld heat treatment (PWHT) or under intermediate to high temperature service conditions. This phenomenon is termed as Stress Relaxation Cracking (SRC) since the purpose of PWHT is to relieve the welding-induced residual stress fields, or as Stress Age Cracking (SAC) if failure happens during service. A leading literature explanation of this failure suggests that the residual stress relaxation and the precipitation dissolution and/or re-precipitation occur in the same temperature range, which can lead to locally high strains and thus to crack at the grain boundaries. Since in situ spatial measurements of residual stress fields, microstructural evolution, and failure processes are nearly infeasible, this work recourses to a micromechanical finite element framework that models the high temperature failure as the nucleation and growth of grain boundary cavities, whereas various parameters such as thermomechanical loading history and its evolution, the competition of grain-interior dislocation creep and grain-boundary diffusion in failure lifetime, and microstructural heterogeneities (such as the precipitate free zone near grain boundaries) can be quantitatively incorporated. It can be concluded from these microstructure-explicit simulations that an accurate knowledge of residual stress evolution and a carefully calibrated set of material constitutive parameters are the essential prerequisites for lifetime predictions. The understanding of individual governing factors also leads to a mechanistic interpretation of the observed SRC susceptibility C-curves. These results suggest that the criticality of residual stress evolution, but not the precipitation-induced local strains, be the leading factor for SRC.

Passivity-based fractionated payload 6-DOF maneuver control using electromagnetic actuation

Employing fractionated spacecraft architecture with electromagnetic actuation into space missions can enhance resilience and flexibility since all subsystems of conventional monolithic spacecraft are separated as several modules to be easily replaced on-orbit when failure happens. Previous electromagnetic configuration used in fractionated spacecraft would render unexpected forces and torques which may undermine the stability of entire system. This paper considers the maneuver of a separated payload in a fractionated spacecraft architecture (FSA) using electromagnetic actuation with adaptive passivity-based control. The FSA consists of a fractionated payload module (FPM) and a supporting spacecraft module (SSM). Relative motion dynamics of FPM and SSM are formulated on SE(3). An adaptive passivity-based 6-DOF motion control scheme is established for FPM's translation and rotation tracking control simultaneously. The closed-loop equilibrium can be attained by the proposed passivity-based 6-DOF control scheme. The controller has no requirement for the precise inertia knowledge of FPM, which processes the robustness of the modelling errors. Numerical simulations are presented to show the effectiveness of the proposed control scheme.

Discoloration on Laser Welds of AISI 321 Tubes

Abstract In this contribution, a fabrication problem is discussed, related to Laser Beam Welding (LBW). Strictly speaking, the case study presented herein does not constitute a failure as such, since the subject components never made it to component service. In the narrow sense of the word, a component failure happens if and when a part does no longer serve its proper function. This is definitely not the case in the study put forward in this paper. However, one could argue that a product that cannot be marketed for lack of certain properties, or because of certain shortcomings, is rendered worthless for the manufacturer and this, in turn, could be considered a failure. In this case study, the issue of discoloration on the surfaces of welded austenitic stainless steel is discussed. This is a well-known and well-researched fabrication problem. Dependent upon service conditions of affected parts, discoloration might be detrimental to the normally outstanding corrosion resistance of this class of high-alloy steels.

Effect of Cooling Rate on Sulfide Stress Cracking Resistance of a Q345 Pressure Vessel Steel Subject to Hydrogen Sulfide

As an important equipment for the separation, store, and transport of the oil and natural gas in energy industry, the pressure vessels are subjected to harsh service environments of sulfide stress cracking (SSC). In this work, the effect of the cooling rate on the SSC susceptibility of a Q345 pressure vessel steel is studied. A pronounced distinction in microstructure is presented as the cooling rate is increased from ≈1 to ≈15 °C s−1. At ≈1 °C s−1, the microstructure is consisted of polygonal‐like ferrite and distinct banded pearlite. At ≈5 °C s−1, the microstructure is consisted of polygonal‐like ferrite and faintly banded pseudo‐pearlite. At ≈15 °C s−1, the microstructure is acicular ferrite with a complete elimination of banded structure. The cooling rate decides the level of the banded structure. As the cooling rate increases, the banded structure becomes relatively slight and even disappears. Strength in sort ascending is ≈1, ≈ 5, and ≈15 °C s−1. The SSC failure happens at ≈1 and ≈5 °C s−1, while does not happen at ≈15 °C s−1. The strength is not the only dominant factor responsible for the SSC failure. The SSC is preferentially generated at the banded structure. The elimination of the banded structure is necessary to improve the SSC resistance of the Q345 pressure vessel steel.

Forecasting failure-prone air pressure systems (FFAPS) in vehicles using machine learning

Vehicles become an inevitable factor in everyone’s life. Sometimes it becomes a threat to human lives and society. For any real-time-based applications, everyone should focus on predicting failure-prone components. A vehicle’s air pressure system (APS) is one of its most important parts. If any system failure happens against APS it leads to core-financial losses, which in turn sometimes leads to loss of human lives. Prediction of APS negligence in a real-time application requires a deep diagnosis and diligent solution. In this study, we developed a machine learning model to predict system failure against APS. A real-time dataset that includes the 170 features and the presence of high-class imbalance data and missing values has been taken and experimentally validated with existing linear and nonlinear classifiers. The performance metrics results show that the Random Forest classifier exceeds other algorithms for training and testing data with an accuracy and F1 score of 99.5 and 99.5 percent respectively.

Mechanical Properties and Fracture Resistance of 3D-Printed Polylactic Acid

Abstract 3D printing is a layer-by-layer deposition process, which results in highly anisotropic structures and contains interfaces. Complex shapes manufactured by 3D printing carry defects. Complete elimination of these defects and interfaces is not possible, and these defects degrade the mechanical properties. In the present study, mechanical properties of printed dog bone samples are quantified as a function of building parameters, in particular, filling patterns, raster angle, and orientation of build direction with respect to that of loading, in polylactic acid (PLA). The tensile strength of 3D-printed PLA is the same for hexagonal and linear pattern filling when the build direction is along thickness and width, and failure was initiated at the defects in the structure, while better overall toughness is offered by hexagonal pattern filling. Build direction along specimen gauge length gives very low tensile strength and toughness, and failure happens between the printing layers. To minimize the defects especially near the grip section, cuboid samples were first deposited and micro-machined by laser into dog bone shape to perform tension test. Tensile strength and elastic modulus of micro-machined samples are surprisingly lower, while failure strain is highest among line filling printed samples. Damage resistance was quantified in terms of work of fracture, and hexagonal filling provided better damage resistance than line filling patterns for conditions of 0 deg raster angle with respect to the crack, whereas line filling with 45 deg and 90 deg raster angle tolerated damage better than hexagonal filling.

Hybrid tree-and-multiple-ring radio-over-fiber transmission system for a 5G network in metropolitan areas

What we believe to be a novel radio-over-fiber (RoF) transmission system with a hybrid tree-and-multiple-ring network structure is developed and experimentally demonstrated to support broadband wireless signal transmission among the central office (CO) and densely distributed 5G base stations (BS) in urban areas. With the assistance of an advanced network structure and a unique single-line bidirectional optical add/drop multiplexer (SBOADM), the transmission system can utilize a hybrid tree-and-ring-topology fiber network to simultaneously support multiple 5G BS-Groups constructed as sub-ring-networks. Furthermore, the system manager is able to simultaneously utilize wavelength/time division multiplexing techniques to support the connected BSs and to dynamically embed extra sub-ring-networks to the main-ring-network or extra BSs to the sub-ring-network by using the RoF transmission system. Needing no backup fiber link, the transmission system enjoys intrinsic robust resilience against fiber link failures. Experimental results proved that the proposed RoF transmission system enables prompt recovery of interrupted optical fiber connection and guarantees the expected quality of service (QoS) by adjusting a few preinstalled optical switches when fiber link failure happens in the main-ring-network, in each sub-ring-network, or even in both of the above scenarios. The induced power penalty for maintaining unchanged bit error rate performance is less than 2 dB. In sum, the proposed transmission system proves to be a great network architecture suitable for supporting 5G signal transmission between the CO and BSs in an urban area due to the dynamically extensible network size and the well-protected transmission that ensures the QoS by simple operation.

Shear strengthening of a concrete trough bridge using embedded through‐section (ETS) FRP bars

AbstractAs worldwide infrastructure is ageing, significant efforts have been paid to the development of strengthening techniques that will restore or increase the initial capacity of existing structures. Considering that it is expected that shear failure happens in a less ductile mode than that observed under bending actions, special attention has been devoted to shear strengthening methods. These methods included externally bonded fiber reinforced polymers (EB‐FRP), near‐surface mounted (NSM‐FRP) method, and the embedded trough‐section (ETS) technique, among others. In this paper, ETS method is used for the strengthening in shear of a reinforced concrete railway bridge located in Finland. The ETS method consists in the embedment of FRP or steel bars through predrilled holes into the concrete core. The bars are bonded to the concrete using adhesives. The paper includes a brief review of recent advances in the use of ETS and comparison with other available techniques, the description of the case study, instrumentation of the bars using fiber optic sensors (FOS) for strain monitoring, the procedure used for the installation of the bars in the field, and a preliminary analysis of the data collected.

Identification of Inability States of Rotating Machinery Subsystems Using Industrial IoT and Convolutional Neural Network – Initial Research

Rotating parts can be found in almost all operational equipment in the industry and are of great importance for proper operation. However, reliability theory explains that every industrial system can change its state when failure happens. Predictive maintenance as one of the latest maintenance strategy emerged from the Maintenance 4.0 concept. Nowadays, this concept can include Industrial Internet of Things (IIoT) devices to connect industrial assets thus enable data collection and analysis that can help make better decisions about maintenance activity. Robust data acquisition system is a prerequisite for any modern predictive maintenance task as it provides necessary data for further analysis and health assessment of the industry asset. Fault diagnosis is an important task in the maintenance of industrial rotating subsystems, considering that early state change diagnosis and fault identification can prevent system failure. Vibration analysis in theory and practice is considered a correct technique for early detection of state changes and failure diagnostics of rotating subsystems. The identified technical state should be considered in a context of the ability and different inability states. Therefore, early different inability states identification is the next step in the rotary machinery diagnostics procedure. Most of the existing techniques for fault diagnosis of rotating subsystems that use vibrations involve the step of extracting features from the raw signal. Considering that the features that describe the behavior of the rotary subsystem can differ significantly depending on the type of equipment, such an approach usually requires an expert in the field of signal processing and rotary subsystems who can define the necessary features. Recently, the emergence of machine deep learning and its application in maintenance promises to provide highly efficient fault diagnostics while simultaneously reducing the need for expert knowledge and human labour. This paper presents authors aim to use self-developed IIoT system built as an IIoT accelerometer as the edge device, web API and database with convolutional neural network as deep learning-based data-driven fault diagnosis to detect and identify different inability states of rotating subsystems. Large dataset for two different rotational speed is collected using IIOT system and multiple convolutional neural network models are trained and tested to examine possibility of using IIOT for inability state prediction.

Evaluating the Integrity of High-Density Polyethylene Storage Tanks

Failure of high-density polyethylene (HDPE) aboveground storage tanks (ASTs) causes numerous environmental, ecological, and economic problems. Therefore, it is necessary to routinely inspect the integrity of ASTs to identify the potential defects and act before a catastrophic failure happens. This study investigated the feasibility of using infrared thermography (IRT) for routine HDPE AST inspections and how weathering impacts the properties of HDPE. Moreover, the factors affecting the IRT’s accuracy for defect detection were researched, and it was attempted to determine the minimum levels of defect detection for each weather circumstance. This study investigated the potential areas for tank failure for close inspection. Results showed that IRT is efficient in detecting shallow defects within the outer half of the wall. The smallest detectable defect size was 2.8 mm, which varied in different measurements depending on the interaction of sample geometry, initial thermal gradient, and defect location.

Reliability analysis for [formula omitted]-out-of-[formula omitted](G) systems subject to dependent competing failure processes

In this paper, reliability analysis for k-out-of-n(G) systems suffering from interdependent competing failure processes is conducted. The system consisting n different components fails if and only if the number of operating components is less than k. Each component degrades linearly with time. A soft failure happens if the total degradation performance exceeds the soft failure threshold of the corresponding component. All components in the system are influenced by random shocks which arrive according to a homogeneous Poisson process. The hard failure of a component occurs when a single shock with large shock load arrives (extreme shock model), or the accumulated shock load of a sequential shocks surpasses the hard failure threshold of the component (cumulative shock model). A component fails if a hard failure or a soft failure occurs. Since the external shock may cause an abrupt degradation increment to a component, the hard failure and soft failure processes of each component are relevant. Moreover, because a shock has impact on all working components in the system, the failure processes of these components are also relevant. Using multivariate analysis methods and techniques, the closed forms of the reliability functions of the k-out-of-n(G) system under the extreme shock model and the cumulative shock model are obtained. Monte Carlo simulation is used as an auxiliary method to compute the system reliability. As a numerical example, the reliability of the micro-electro-mechanical systems is calculated to illustrate the developed theory.

Survival Rate Analysis of Heart Failure Patients at Arbaminch General Hospital, Southern Ethiopia, 2022

Chronic heart failure happens when the heart’s muscle is incapable of circulate sufficient blood to satisfy the requirements of the body for both oxygen and blood. In other sense, the heart is overwhelmed by its load. The goal of this study is to pinpoint the risk variables accountable for the variability in congestive heart failure patients’ survival times from January 2017 to December 2021 at ArbaMinch General Hospital in South Ethiopia. Utilizing cox proportional hazard models, the data was examined. A retrospective investigation was conducted. Data was gathered from the cards of 199 congestive heart failure patients who were being followed up on using a straightforward random sampling approach. We discovered that 21.6 percent of the 199 patients with congestive heart failure investigated died, while the remaining 78.4% were censoring. Patients’ mean baseline left ventricular ejection fraction was 43.18 percent (with a standard deviation of 13.928 percent), implying that each pulse expels 43.18 percent of the blood in the left ventricle. Patients with heart failure who tested positive for tuberculosis had a substantially increased chance of death. Left ventricular ejection fraction, tuberculosis, diabetes militias, etiology of heart failure, type of congestive heart failure, smoking status, and chorionic kidney disease were originate to be significant risk factors for death in patients with congestive heart failure. As a result, physicians are encouraged to pay greater attention to heart failure patients.

Evaluation of tensile properties of early-age concrete-block masonry assemblages

Masonry is one of the most traditional and economical modes of construction worldwide. Although many codes and standards are available to evaluate fully-cured masonry assembly properties for the design of masonry structures, there is a gap in understanding the properties of freshly laid masonry and the design of newly constructed unsupported masonry walls. Early-age (within the first seven days) masonry at the construction site possesses reasonably high compressive strength but considerably low flexural tensile strength, making it vulnerable to lateral loads due to wind, earthquake, and adjacent constructions. This has resulted in numerous incidents of structural damage and injury to workers leading to more stringent and conservative construction bracing techniques. In this paper, the tensile properties of early-age concrete block masonry have been assessed by conducting comprehensive numerical and experimental studies on mortar and masonry assemblage. Outlier analysis has been applied to the experimental data to minimize uncertainties and biases. The modulus of elasticity and tensile strength of the masonry assemblages against the curing time has been obtained using a statistical analysis conducted over a large sample size. The results show that the tensile strength of masonry remains nearly insignificant until 3–7 h, then increases logarithmically. It is also observed that the bond between the mortar and blocks is the weakest part of the masonry assemblages, and the failure happens in the unit-mortar interface bond rather than in the fresh mortar. The modulus of elasticity and tensile strength of early-age masonry assemblages are 38% and 18% of the corresponding properties of early-age mortar material alone, respectively. Therefore, the quantification of assembly properties cannot be ascertained from material testing alone within seven days of construction. It is anticipated that the proposed research will provide valuable design properties leading to improved guidelines needed to design control devices (e.g., temporary bracing) for concrete-block masonry construction.

Patient-Friendly Summary of the ACR Appropriateness Criteria®: Renal Failure.

Renal (kidney) failure occurs when one or both kidneys do not function well. Acute kidney failure happens suddenly and can be temporary or progress to chronic failure. Chronic kidney failure is persistent and can slowly worsen over time. In general, contrast should be avoided in kidney failure, unless medically necessary.

Dynamic behavior of single curved fiber-metal hybrid lamina composite shells under blast loading-experimental observations

In the current study, the dynamic response of single curved fiber-metal hybrid lamina composite (FM-HLC) shells under blast loading was experimentally investigated. The influence of explosive mass and distance, the weave pattern of fiber-metal hybrid lamina, and the radius of curvature was analyzed. The experimental results show that the deformation modes of curved FM-HLC shells under blast are similar to that of metal shells when failure is absent. After failure happens, severe delamination only occurs at the site of damage region rather than extending to other area. This strongly demonstrates that FM-HLC shells have better anti-delamination performance than traditional FMLs when subject to blast loads. For different weave patterns, the global deformation of FM-HLCs decreases with the increase of longitudinal reinforcement level. When the radius of curvature increases from 250 mm to infinity (flat panel), the permanent deflection of the structure gradually increases. Meanwhile, the “counter-intuitive behavior” and “local reverse snap buckling” are observed in the experiments. This work not only provides a strategy for blast resistance design of FM-HLCs, but also offers a good reference for understanding the response of orthotropic panels/shells under blast impact.

Novel Method of Characterization of Heart Disease Prediction Using Sequential Feature Selection-Based Ensemble Technique

The exact forecast of heart disease is necessary to proficiently treating cardiovascular patients before a heart failure happens. Assuming we talk about artificial intelligence (AI) techniques, can be accomplished utilizing an ideal AI model with rich medical services information on heart diseases. To begin with, the feature extraction technique, gradient boosting-based sequential feature selection (GBSFS) is applied to separate the significant number of features from coronary illness dataset to create important medical services information. Using machine learning algorithms like Decision tree (DT), Random forest (RF), Multilayer perceptron (MLP), Support vector machine (SVM), Extra tree (ET), Gradient boosting (GBC), Linear regression (LR), K-nearest neighbor (KNN), and stacking, a comparison model is created between dataset that include both all features and a significant number of features. With stacking, the proposed framework achieves test accuracy of 98.78 percent, which is higher than the existing frameworks and most notable in the marking model with 11 features. This outcome shows that our framework is more powerful for the expectation of coronary illness, in contrast with other cutting edge strategies.